Non-uniform line-of-sight measurements of nitric oxide using mid-infrared Faraday rotation spectroscopy.

Traditional absorption spectroscopy relies on detecting intensity variations along the line-of-sight to gauge average concentration and temperature. While methods like profile fitting and temperature binning offer insights into the non-uniformity of the path, they fall short of accurately capturing the precise spatial distribution with a single line-of-sight measurement. We propose a novel measurement scheme for non-uniformly distributed concentration of nitric oxide (NO) along the line-of-sight utilizing a single laser and path, by incorporating Faraday rotation spectroscopy with magnetic fields changing over time and space.

Facilitating COVID recognition from X-rays with computer vision models and transfer learning.

Multimedia data plays an important role in medicine and healthcare since EHR (Electronic Health Records) entail complex images and videos for analyzing patient data. In this article, we hypothesize that transfer learning with computer vision can be adequately harnessed on such data, more specifically chest X-rays, to learn from a few images for assisting accurate, efficient recognition of COVID. While researchers have analyzed medical data (including COVID data) using computer vision models, the main contributions of our study entail the following.

Electrochemically Grown Ultrathin Platinum Nanosheet Electrodes with Ultralow Loadings for Energy-Saving and Industrial-Level Hydrogen Evolution.

Nanostructured catalyst-integrated electrodes with remarkably reduced catalyst loadings, high catalyst utilization and facile fabrication are urgently needed to enable cost-effective, green hydrogen production via proton exchange membrane electrolyzer cells (PEMECs). Herein, benefitting from a thin seeding layer, bottom-up grown ultrathin Pt nanosheets (Pt-NSs) were first deposited on thin Ti substrates for PEMECs via a fast, template- and surfactant-free electrochemical growth process at room temperature, showing highly uniform Pt surface coverage with ultralow loadings and vertically well-aligned nanosheet morphologies. Combined with an anode-only Nafion 117 catalyst-coated membrane (CCM), the Pt-NS electrode with an ultralow loading of 0.

Discovering Reactant Supply Pathways at Electrode/PEM Reaction Interfaces Via a Tailored Interface-Visible Characterization Cell.

In situ and micro-scale visualization of electrochemical reactions and multiphase transports on the interface of porous transport electrode (PTE) materials and solid polymer electrolyte (SPE) has been one of the greatest challenges for electrochemical energy conversion devices, such as proton exchange membrane electrolyzer cells (PEMECs), CO reduction electrolyzers, PEM fuel cells, etc. Here, an interface-visible characterization cell (IV-CC) is developed to in situ visualize micro-scaled and rapid electrochemical reactions and transports in PTE/SPE interfaces. Taking the PEMEC of a green hydrogen generator as a study case, the unanticipated local gas blockage, micro water droplets, and their evolution processes are successfully visualized on PTE/PEM interfaces in a practical PEMEC device, indicating the existence of unconventional reactant supply pathways in PEMs.

Robust Copper-Based Nanosponge Architecture Decorated by Ruthenium with Enhanced Electrocatalytic Performance for Ambient Nitrogen Reduction to Ammonia.

Electrochemical conversion of nitrogen to green ammonia is an attractive alternative to the Haber-Bosch process. However, it is currently bottlenecked by the lack of highly efficient electrocatalysts to drive the sluggish nitrogen reduction reaction (NRR). Herein, we strategically design a cost-effective bimetallic Ru-Cu mixture catalyst in a nanosponge (NS) architecture a rapid and facile method.

Prediction-Based Human-Robot Collaboration in Assembly Tasks Using a Learning from Demonstration Model.

Most robots are programmed to carry out specific tasks routinely with minor variations. However, more and more applications from SMEs require robots work alongside their counterpart human workers. To smooth the collaboration task flow and improve the collaboration efficiency, a better way is to formulate the robot to surmise what kind of assistance a human coworker needs and naturally take the right action at the right time.

Y-Net: a dual-branch deep learning network for nonlinear absorption tomography with wavelength modulation spectroscopy.

This paper demonstrates a new method for solving nonlinear tomographic problems, combining calibration-free wavelength modulation spectroscopy (CF-WMS) with a dual-branch deep learning network (Y-Net). The principle of CF-WMS, as well as the architecture, training and performance of Y-Net have been investigated. 20000 samples are randomly generated, with each temperature or HO concentration phantom featuring three randomly positioned Gaussian distributions.

Tuning Catalyst Activation and Utilization Via Controlled Electrode Patterning for Low-Loading and High-Efficiency Water Electrolyzers.

An anode electrode concept of thin catalyst-coated liquid/gas diffusion layers (CCLGDLs), by integrating Ir catalysts with Ti thin tunable LGDLs with facile electroplating in proton exchange membrane electrolyzer cells (PEMECs), is proposed. The CCLGDL design with only 0.08 mg cm can achieve comparative cell performances to the conventional commercial electrode design, saving ≈97% Ir catalyst and augmenting a catalyst utilization to ≈24 times.

Exploring the Impacts of Conditioning on Proton Exchange Membrane Electrolyzers by Visualization and Electrochemistry Characterization.

For a proton exchange membrane electrolyzer cell (PEMEC), conditioning is an essential process to enhance its performance, reproducibility, and economic efficiency. To get more insights into conditioning, a PEMEC with Ir-coated gas diffusion electrode (IrGDE) was investigated by electrochemistry and visualization characterization techniques. The changes of polarization curves, electrochemical impedance spectra (EIS), and bubble dynamics before and after conditioning are analyzed.

Intelligent fluorescence image analysis of giant unilamellar vesicles using convolutional neural network.

Background: Fluorescence image analysis in biochemical science often involves the complex tasks of identifying samples for analysis and calculating the desired information from the intensity traces. Analyzing giant unilamellar vesicles (GUVs) is one of these tasks. Researchers need to identify many vesicles to statistically analyze the degree of molecular interaction or state of molecular organization on the membranes.

Engineered Thin Diffusion Layers for Anion-Exchange Membrane Electrolyzer Cells with Outstanding Performance.

Anion-exchange membrane electrolyzer cells (AEMECs) are one of the most promising technologies for carbon-neutral hydrogen production. Over the past few years, the performance and durability of AEMECs have substantially improved. Herein, we report an engineered liquid/gas diffusion layer (LGDL) with tunable pore morphologies that enables the high performance of AEMECs.

Optical properties of anatase and rutile TiO films deposited by using a pulsed laser.

Transparent titanium dioxide () films were deposited on quartz substrates by using a pulsed-laser deposition technique. The effects of deposition temperatures on the crystalline phases and optical properties of the films were investigated. Phase-pure anatase and rutile films were obtained at temperatures of 600°C and 800°C, respectively.

Gaussian process regression for direct laser absorption spectroscopy in complex combustion environments.

Tunable diode laser absorption spectroscopy (TDLAS) has been proved to be a powerful diagnostic tool in combustion research. However, current methods for post-processing a large number of blended spectral lines are often inadequate both in terms of processing speed and accuracy. The present study verifies the application of Gaussian process regression (GPR) on processing direct absorption spectroscopy data in combustion environments to infer gas properties directly from the absorbance spectra.

Constructing Ultrathin W-Doped NiFe Nanosheets via Facile Electrosynthesis as Bifunctional Electrocatalysts for Efficient Water Splitting.

Exploring cost-effective and efficient bifunctional electrocatalysts via simple fabrication strategies is strongly desired for practical water splitting. Herein, an easy and fast one-step electrodeposition process is developed to fabricate W-doped NiFe (NiFeW)-layered double hydroxides with ultrathin nanosheet features at room temperature and ambient pressure as bifunctional catalysts for water splitting. Notably, the NiFeW nanosheets require overpotentials of only 239 and 115 mV for the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), respectively, to reach a current density of 10 mA/cm in alkaline media.

Functional Modular Network Identifies the Key Genes of Preoperative Inhalation Anesthesia and Intravenous Anesthesia in Off-Pump Coronary Artery Bypass Grafting.

Off-pump coronary artery bypass grafting (OPCABG) is an effective strategy for revascularization. Preoperative anesthesia appears critical due to surgical instability and the risk of organ damage. This study, based on a functional module network, analysed the effects of preoperative inhalation anesthesia and intravenous anesthesia on OPCABG and performed a pivot analysis of its potential drug regulators.

Picosecond nonlinear optical properties of SrTiO composite films doped with gold and nickel nanoparticles.

Nanoparticles composite thin films formed by nanometer-sized gold and nickel particles embedded in SrTiO matrices were fabricated on MgO single-crystal substrates by co-depositing the metal and ceramic targets using the pulsed laser deposition technique. The linear optical absorption properties were measured from 350 to 800 nm, and the absorption peak due to the surface plasmon resonance of Au metal particles was observed around 557 nm. The ultra-fast third-order nonlinear optical properties of the films were determined by a single-beam z-scan method at a wavelength of 532 nm with laser duration of 55 ps.

Nonlinear refraction and saturable absorption in Au:BaTiO3 composite films.

Composite thin films Au:BaTiO3, comprising nanometer-sized gold particles embedded in barium titanate matrices, were synthesized on MgO (100) substrates with the pulsed laser deposition technique. The nanostructure of the films and the size distributions of the Au particles were analyzed by high-resolution transmission electron microscopy. Crystal lattice fringes from the Au nanocrystals and the BaTiO3 matrices were observed.